In this paper we describe our recent research efforts towards reliable and automatic generation of indices for use in content understanding of video. Following our earlier research in temporal shot segmentation of video, we have developed a comprehensive system framework for segmenting an unconstrained variety of text from general purpose broadcast video. In addition, the framework also contain...

In this paper, we present an automated video analysis system which addresses segmentation and detection of human actions in an indoor environment, such as a gym. The system aims at segmenting different movements from the input video and recognizing the action types simultaneously. Two action segmentation techniques, namely color intensity based and motion based, are proposed. Both methods can e...

The paper proposes a novel algorithm to dynamically define the Region of Interest (ROI) videophone application. The algorithm uses the color information Hue and Cr to find the skincolor pixels and also use range of threshold obtained from red and blue components in normalized RGB color space to remove nonskincolor pixels because the human skin tends to have a predominance of red and non-predomi...

We propose an unsupervised video object segmentation algorithm that detects recurring objects and learns cohort object proposals over space-time. Our core contribution is a graph transduction process that learns object proposals densely over space-time, exploiting both appearance models learned from rudimentary detections of sparse objectlike regions, and their intrinsic structures. Our approac...

Video coding schemes rely on motion estimation and compensation methods to exploit temporal redundancies. Due to their simplicity and low overhead information, block matching techniques are widely used. They however induce annoying artifacts due the hypothesis of uniform motion within each block. In this paper, a VQ-based segmentation entailing a re nement of the motion eld is proposed. The seg...

This paper investigates motion estimation and segmentation of independently moving objects in video sequences that contain depth and intensity information, such as videos captured by a Time of Flight camera. Specifically, we present a motion estimation algorithm which is based on integration of depth and intensity data. The resulting motion information is used to derive long-term point trajecto...

We present an online video segmentation algorithm based on a novel nonparametric Bayesian clustering method called Bayesian Split-Merge Clustering (BSMC). BSMC can efficiently cluster dynamically changing data through split and merge processes at each time step, where the decision for splitting and merging is made by approximate posterior distributions over partitions with Dirichlet Process (DP...

A methodology for the segmentation of successive frames of a video sequence is presented. Traditional methods, treating each frame in isolation, are computationally expensive, ignore potentially useful information derived from previous frames, and can lead to instabilities in the segmentation over the sequence. The approach developed here, based on the Region Competition algorithm (Zhu and Yuil...

Video segmentation has been used in a variety of computer vision algorithms as a pre-processing step. Despite its wide application, many existing algorithms require preloading all or part of the video and batch processing the frames, which introduces temporal latency and significantly increases memory and computational cost. Other algorithms rely on human specification for segmentation granular...